Identification of causal effects in case-control studies

PubMed Central

Abstract

BACKGROUND: Case-control designs are an important yet commonly misunderstood tool in the epidemiologist’s arsenal for causal inference. We reconsider classical concepts, assumptions and principles and explore when the results of case-control studies can be endowed a causal interpretation. RESULTS: We establish how, and under which conditions, various causal estimands relating to intention-to-treat or per-protocol effects can be identified based on the data that are collected under popular sampling schemes (case-base, survivor, and risk-set sampling, with or without matching). We present a concise summary of our identification results that link the estimands to the (distribution of the) available data and articulate under which conditions these links hold. CONCLUSION: The modern epidemiologist’s arsenal for causal inference is well-suited to make transparent for case-control designs what assumptions are necessary or sufficient to endow the respective study results with a causal interpretation and, in turn, help resolve or prevent misunderstanding. Our approach may inform future research on different estimands, other variations of the case-control design or settings with additional complexities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12874-021-01484-7).

Authors 2

1. Bas B. L. Penning de Vries Aachen Department of Clinical Epidemiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, PO Box 9600, 2300 RC, The Netherlands

2. Rolf H. H. Groenwold Aachen Department of Clinical Epidemiology

   Leiden University Medical Center

   Affiliation as printed

   Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, PO Box 9600, 2300 RC, The Netherlands